Co-occurrence of resonant activation and noise-enhanced stability in a model of cancer growth in the presence of immune response

Noise exposure and the risk of cancer: a comprehensive systematic review

The association between noise exposure and increased risk of cancer has received little attention in the field of research. Therefore, the goal of this study was to conduct a systematic review on the relationship between noise exposure and the incidence of cancer in humans. In this study, four electronic bibliographic databases including Scopus, PubMed, Web of Science, and Embase were systematically searched up to 21 April 2022. All types of noise exposure were considered, including environmental noise, occupational noise, and leisure or recreational noise. Furthermore, all types of cancers were studied, regardless of the organs involved. In total, 1836 articles were excluded on the basis of containing exclusion criteria or lacking inclusion criteria, leaving 19 articles retained for this study. Five of nine case-control studies showed a significant relationship between occupational or leisure noise exposure and acoustic neuroma. Moreover, four of five case-control and cohort studies indicated statistically significant relationships between environmental noise exposure and breast cancer. Of other cancer types, two case-control studies highlighted the risk of Hodgkin and non-Hodgkin lymphoma and two cohort studies identified an increased risk of colon cancer associated with environmental noise exposure. No relationship between road traffic and railway noise and the risk of prostate cancer was observed. In total, results showed that noise exposure, particularly prolonged and continuous exposure to loud noise, can lead to the incidence of some cancers. However, confirmation of this requires further epidemiological studies and exploration of the exact biological mechanism and pathway for these effects.

Effect of color cross-correlated noise on the growth characteristics of tumor cells under immune surveillance

Based on the Michaelis-Menten reaction model with catalytic effects, a more comprehensive one-dimensional stochastic Langevin equation with immune surveillance for a tumor cell growth system is obtained by considering the fluctuations in growth rate and mortality rate. To explore the impact of environmental fluctuations on the growth of tumor cells, the analytical solution of the steady-state probability distribution function of the system is derived using the Liouville equation and Novikov theory, and the influence of noise intensity and correlation intensity on the steady-state probability distributional function are discussed. The results show that the three extreme values of the steady-state probability distribution function exhibit a structure of two peaks and one valley. Variations of the noise intensity, cross-correlation intensity and correlation time can modulate the probability distribution of the number of tumor cells, which provides theoretical guidance for determining treatment plans in clinical treatment. Furthermore, the increase of noise intensity will inhibit the growth of tumor cells when the number of tumor cells is relatively small, while the increase in noise intensity will further promote the growth of tumor cells when the number of tumor cells is relatively large. The color cross-correlated strength and cross-correlated time between noise also have a certain impact on tumor cell proliferation. The results help people understand the growth kinetics of tumor cells, which can a provide theoretical basis for clinical research on tumor cell growth.

Interplay of noise induced stability and stochastic resetting

Stochastic resetting and noise-enhanced stability are two phenomena that can affect the lifetime and relaxation of nonequilibrium states. They can be considered measures of controlling the efficiency of the completion process when a stochastic system has to reach the desired state. Here, we study the interaction of random (Poissonian) resetting and stochastic dynamics in unstable potentials. Unlike noise-induced stability that increases the relaxation time, the stochastic resetting may eliminate winding trajectories contributing to the lifetime and accelerate the escape kinetics from unstable states. In this paper, we present a framework to analyze compromises between the two contrasting phenomena in noise-driven kinetics subject to random restarts.

Dichotomous flow with thermal diffusion and stochastic resetting

We consider properties of one-dimensional diffusive dichotomous flow and discuss effects of stochastic resonant activation (SRA) in the presence of a statistically independent random resetting mechanism. Resonant activation and stochastic resetting are two similar effects, as both of them can optimize the noise-induced escape. Our studies show completely different origins of optimization in adapted setups. Efficiency of stochastic resetting relies on elimination of suboptimal trajectories, while SRA is associated with matching of time scales in the dynamic environment. Consequently, both effects can be easily tracked by studying their asymptotic properties. Finally, we show that stochastic resetting cannot be easily used to further optimize the SRA in symmetric setups.

Noise-induced bistability in the fate of cancer phenotypic quasispecies: a bit-strings approach

Tumor cell populations are highly heterogeneous. Such heterogeneity, both at genotypic and phenotypic levels, is a key feature during tumorigenesis. How to investigate the impact of this heterogeneity in the dynamics of tumors cells becomes an important issue. Here we explore a stochastic model describing the competition dynamics between a pool of heterogeneous cancer cells with distinct phenotypes and healthy cells. This model is used to explore the role of demographic fluctuations on the transitions involving tumor clearance. Our results show that for large population sizes, when demographic fluctuations are negligible, there exists a sharp transition responsible for tumor cells extinction at increasing tumor cells' mutation rates. This result is consistent with a mean field model developed for the same system. The mean field model reveals only monostability scenarios, in which either the dominance of the tumor cells or the dominance of the healthy cells is found. Interestingly, the stochastic model shows that for small population sizes the monostability behavior disappears, involving the presence of noise-induced bistability. The impact of the initial populations of cells in the fate of the cell populations is investigated, as well as the transient times towards the healthy and the cancer states.

A computable evolution equation for the joint response-excitation probability density function of stochastic dynamical systems

By using functional integral methods, we determine a computable evolution equation for the joint response-excitation probability density function of a stochastic dynamical system driven by coloured noise. This equation can be represented in terms of a superimposition of differential constraints, i.e. partial differential equations involving unusual limit partial derivatives, the first one of which was originally proposed by Sapsis & Athanassoulis. A connection with the classical response approach is established in the general case of random noise with arbitrary correlation time, yielding a fully consistent new theory for non-Markovian systems. We also address the question of computability of the joint response-excitation probability density function as a solution to a boundary value problem involving only one differential constraint. By means of a simple analytical example, it is shown that, in general, such a problem is undetermined, in the sense that it admits an infinite number of solutions. This issue can be overcome by completing the system with additional relations yielding a closure problem, which is similar to the one arising in the standard response theory. Numerical verification of the equations for the joint response-excitation density is obtained for a tumour cell growth model under immune response.

Resonant activation in piecewise linear asymmetric potentials

This work analyzes numerically the role played by the asymmetry of a piecewise linear potential, in the presence of both a Gaussian white noise and a dichotomous noise, on the resonant activation phenomenon. The features of the asymmetry of the potential barrier arise by investigating the stochastic transitions far behind the potential maximum, from the initial well to the bottom of the adjacent potential well. Because of the asymmetry of the potential profile together with the random external force uniform in space, we find, for the different asymmetries: (1) an inversion of the curves of the mean first passage time in the resonant region of the correlation time τ of the dichotomous noise, for low thermal noise intensities; (2) a maximum of the mean velocity of the Brownian particle as a function of τ; and (3) an inversion of the curves of the mean velocity and a very weak current reversal in the miniratchet system obtained with the asymmetrical potential profiles investigated. An inversion of the mean first passage time curves is also observed by varying the amplitude of the dichotomous noise, behavior confirmed by recent experiments.

Thermal-inertial ratchet effects: negative mobility, resonant activation, noise-enhanced stability, and noise-weakened stability

Transport properties of a Brownian particle in thermal-inertial ratchets subject to an external time-oscillatory drive and a constant bias force are investigated. Since the phenomena of negative mobility, resonant activation and noise-enhance stability were reported before, in the present paper, we report some additional aspects of negative mobility, resonant activation and noise-enhance stability, such as the ingredients for the appearances of these phenomena, multiple resonant activation peaks, current reversals, noise-weakened stability, and so on.

Noise-induced enhancement of stability in a metastable system with damping

The mean first passage time of a Brownian particle from an initial unstable state in a metastable system with damping is investigated. The system is analyzed in the low to high damping regime, and the role played by the damping parameter is studied. We observe the noise enhanced stability effect for all the initial unstable states under study and for all values of the damping parameter γ investigated. The curves show a behavior of the mean first passage time vs γ very close to that observed for an overdamped particle in the presence of colored noise as a function of the correlation time.

Stability measures in metastable states with Gaussian colored noise

We present a study of the escape time from a metastable state of an overdamped Brownian particle in the presence of colored noise generated by Ornstein-Uhlenbeck process. We analyze the role of the correlation time on the enhancement of the mean first passage time through a potential barrier and on the behavior of the mean growth rate coefficient as a function of the noise intensity. We observe the noise-enhanced stability effect for all the initial unstable states used and for all values of the correlation time tau(c) investigated. We can distinguish two dynamical regimes characterized by weak and strong correlated noises, depending on the value of tau(c) with respect to the relaxation time of the system.